Cells in a population are in many aspects unique in their characteristics, even in a seemingly homogenous culture or tissue. Gene expression levels show large cell-cell variations, due to external (extrinsic) and internal (intrinsic) sources of factors. Likewise, when exposed to identical stimuli, cells often behave stochastically. This means that data obtained from a population of cells can not be assumed to reflect the behavior of the individual cell. It has been suggested that cells can respond to stimuli by bursts in transcriptional activity and operate as a binary switch; that is in an all-or-none fashion.
To determine whether two transcripts are expressed in a parallel (expression high at the same time) or anti-parallel (one is high when the other is low), transcription analysis at the level of the individual cell is required. When groups of cells are analyzed at the same time, important information is lost. For example, it is not possible to discriminate between a small change in gene transcription occurring in every cell as opposed to major changes in only a few cells. Furthermore, cell heterogeneity in tissues makes cell-type specific analysis difficult. These issues are resolved by measurements in individual cells.
A typical eukaryotic cell contains about 25 pg of RNA of which less than 2% is mRNA. This corresponds to a few hundred thousands of transcripts of the 10,000 genes that are expressed in each cell at any particular point in time. Imaging techniques such as multiplex fluorescent in situ-hybridization (FISH) can monitor gene transcriptional activity spatially within a single cell by labeling of specific mRNAs and may be applied to living cells to provide temporally resolved glimpses of the complexity of the transcription machinery. Protein levels in single cells have been measured quantitatively in bacteria and yeast using fluorescent reporter proteins. For a complete transcriptome analysis of a single cell, microarrays, preceded by non-specific amplification of cDNA, are used. The most widespread method for single cell mRNA analysis is reverse transcription polymerase chain reaction (RT-PCR), and the related quantitative real-time RT-PCR (qRT-PCR). This technique offers superior sensitivity, accuracy, and dynamic range compared to alternative methods for mRNA measurements. The number of transcripts that can be readily analyzed in the single cell is small, but pre-amplification of cDNA vastly increases this number.
However, the protocols for single cell analysis that exist in the art so far are useful only with respect to the detection of abundantly expressed targets. These methods do not provide the sensitivity required to detect target mRNAs that are expressed as a comparatively low level.